1. Technical Field
This invention is directed toward a fully automatic system and method for modeling objects from an image. More specifically, the invention is directed toward a fully automatic system and method for modeling three-dimensional objects, such as faces, from a single image.
2. Background Art
There has been much work on face modeling from images. One technique which has been used in many commercial systems employs two orthogonal views—one frontal view and one side view in order to create a face model. This type of system requires the user to manually specify the face features on the two images in order to model the face. There are, however, some of these face-modeling systems employing more than one input image that have attempted to employ some feature finding methods to reduce the amount of manual work necessary to create the resulting model.
Another type of face modeling system creates face models from a video sequence. Since this type of system has available images of multiple views of the face to be modeled, it can potentially compute the correct depth and can generate a texture image for an entire face. However, this type of system requires the user to have a video camera. In addition, this type of system requires some amount of user input to render accurate models and make it robust.
Another approach to generating face models from a single image, described by V. Blanz and T. Vetter [1], requires the use of both a geometry database and an image database to generate three-dimensional (3D) models. However, this approach can only model the people whose skin types are covered by the database. In this approach, the database used mainly consisted of Caucasian people. Therefore, it is difficult to model people of other races. It would require an extremely large image database to cover people of all races. Another problem with this modeling approach is that the images in the database contain the lighting conditions when those images were taken. Given a new image, its lighting condition is in general different from the lighting condition in the database. The approach described by Blanz et al. employs a linear method to adjust the lighting, but lighting condition changes cannot be modeled very well by a linear technique. Therefore, the system has difficulties in handling arbitrary lighting conditions. In addition, it requires manual initialization to provide the location of the face, its pose, and face features. Hence, the system is not fully automatic. Finally, this system is computationally expensive and not very robust because it has a large amount of unknowns, must perform a large number of image operations, and a large percentage of the equations used are highly nonlinear.
What is needed is a system that can create a 3D model of a face, or similar object, using a single image, that does not require user interaction, is fast and computationally efficient, can model people of any skin types in various lighting conditions, and is robust.